Work with us

Kaggle is the world’s largest data science and machine learning community. Our community of more than one million users come to Kaggle to learn, compete, and collaborate on the cutting edge of machine learning. We are best known for running machine learning competitions, for hosting public datasets, and for our cloud-based data science workbench (Kaggle Kernels).

In our next chapter, we aim to make Kaggle the place where data scientists do all of their work across competitions, open datasets, and academic/commercial problems. We’ll also be focussed on exposing GCP machine learning services to our community.

Kaggle was acquired by Google earlier this year and will continue to operate as an independent brand. We retain a startup ethos: you will have a lot of autonomy, your work will have a major impact, and we work quickly on a big range of interesting problems.

Kaggle has been built from the ground up with a strong commitment to remote work. Our team is distributed across the US and Australia, and includes people in the Google SF, MTV, Kirkland, NYC, and Sydney offices. We encourage applications from candidates working out of any office or remote location within North American timezones. We encourage flexible working arrangements, to find the work/life balance that suits you.

What does the role involve?

As a Kaggle data scientist, you will be crucial to the company’s mission. You will work with customers from both the commercial and research worlds to prepare their competitions and address a range of challenges from problem identification to data cleaning and exploration, to managing the live competition, as well as building tools to help automate this process. Your role will go to the heart of Kaggle’s value in the data science world.

Kaggle data scientists have access to a huge range of data sets and customers. Over the few years, we have worked on data sets relating to:

airline flight arrivals and flight route optimization

energy disaggregation to predict which household appliances are in use